Cloud‑Driven AI/ML Infrastructure Engineer

Placements24; LegKraal Gate; Hybrid; ZAR 900,000 - 1,500,000; Full time

Benefits offered by this job

Competitive salary

Performance-based bonuses

Health, dental, and vision insurance

Professional development opportunities

Access to cutting-edge infrastructure

Job summary

Placements24 seeks an AI/ML Infrastructure Engineer to build scalable cloud-based platforms powering AI initiatives in Mahikeng. You will design, implement, and manage robust ML infra, focusing on reliability, performance, and cost efficiency to support data scientists and ML engineers.

You will collaborate closely with AI teams, implement MLOps pipelines, and ensure security and observability of the infrastructure across AWS/Azure/GCP environments.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or related field.
• 3+ years of experience in DevOps, SRE, or infrastructure engineering with AI/ML focus.
• Proficiency with cloud platforms (AWS, Azure, GCP).
• Experience with Docker and Kubernetes.
• Strong CI/CD knowledge (Jenkins, GitLab CI).
• IaC experience with Terraform and Ansible.

Responsibilities

• Design, build, and maintain scalable AI/ML infra on cloud platforms (AWS/Azure/GCP).
• Implement and manage MLOps pipelines for CI/CD, testing, deployment, and monitoring.
• Optimize resources for cost-effectiveness and performance for ML workloads.
• Develop and manage Docker and Kubernetes ecosystems for ML apps.
• Ensure security, stability, and observability of AI/ML infrastructure.
• Collaborate with data scientists/ML engineers to support infra needs.

Skills

DevOps

SRE

Cloud proficiency

CI/CD

Education

Bachelor's degree in Computer Science or related field

Tools

Docker

Kubernetes

Terraform

Ansible

Jenkins

GitLab CI

Job description

Placements24 seeks an AI/ML Infrastructure Engineer to build scalable cloud-based platforms powering AI initiatives in Mahikeng. You will design, implement, and manage robust ML infra, focusing on reliability, performance, and cost efficiency to support data scientists and ML engineers.

You will collaborate closely with AI teams, implement MLOps pipelines, and ensure security and observability of the infrastructure across AWS/Azure/GCP environments.